Development of computer vision algorithms for tissue identification and segmentation in medical ultrasound images

开发用于医学超声图像中组织识别和分割的计算机视觉算法

• 批准号: 238766-2006
• 负责人: Linney, Norma
• 金额: $ 0.73万
• 依托单位: Saint Mary's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2006
• 资助国家: 加拿大
• 起止时间: 2006-01-01 至 2007-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=338403
• 关键词: Development; computer; vision; algorithms; tissue

Ultrasound is one of the more patient friendly medical imaging modalities. It is the modality of choice for infants as the equipment can be brought to the bassinette or incubator and administered with minimal disturbance or side effects to the infant. Similarly the equipment can easily be brought to adult patients and the procedure is well tolerated by the extremely ill. However, ultrasound images contain speckle and noise making the extraction of diagnostic information from these images more challenging than for other imaging modalities. The goal of this research project is to develop automated software tools that will help the physician extract relevant diagnostic information from these ultrasound images. In particular to develop an automated technique for the identification and characterization of tissue types so that ultimately healthy tissue can be reliably distinguished from unhealthy tissue. Improving the viability of using a more patient friendly imaging modality while still achieving the same or better clinical results will have a significant impact on patient health and health care costs.

超声波是更耐心的医学成像方式之一。这是婴儿的选择方式，因为可以将设备带到巴西内特或孵化器，并给婴儿带来最小的干扰或副作用。同样，设备很容易被带给成年患者，并且该手术受到了极度病的耐受性。但是，超声图像包含斑点和噪音，从这些图像中提取诊断信息比其他成像方式更具挑战性。该研究项目的目的是开发自动化软件工具，以帮助医生从这些超声图像中提取相关的诊断信息。特别是开发一种自动化技术来鉴定和表征组织类型，以便最终可以可靠地与不健康的组织区分开。提高使用更具患者友好的成像方式同时达到相同或更好的临床结果的生存能力将对患者的健康和医疗保健费用产生重大影响。